Removed von Mises constraint

git-svn-id: https://pymc.googlecode.com/svn/trunk@1162 15d7aa0b-6f1a-0410-991a-d59f85d14984

code_maintenance.py

@@ -25,19 +25,19 @@ def remove_whitespace(fname):
     for line in lines:
         fd.write(line+'\n')
     fd.close()
-    print 'Removed whitespace from %s'%fname
+    # print 'Removed whitespace from %s'%fname
 
-print
+# print
 
 # ====================
 # = Strip whitespace =
 # ====================
 for dirname, dirs, files in os.walk('.'):
     if dirname[1:].find('.')==-1:
-        print dirname
+        # print dirname
         for fname in files:
             if fname[-2:] in ['c', 'f'] or fname[-3:]=='.py' or fname[-4:] in ['.pyx', '.txt', '.tex', '.sty', '.cls'] or fname.find('.')==-1:
-                print fname
+                # print fname
                 remove_whitespace(dirname + '/' + fname)
 
 # ==========================

pymc/CommonDeterministics.py

@@ -411,12 +411,12 @@ def coef(index=self.index, x=x):
 def pfunc(func):
     """
     pf = pfunc(func)
-    
+
     Returns a function that can be called just like func; however its arguments may be
     PyMC objects or containers of PyMC objects, and its return value will be a deterministic.
-    
+
     Example:
-    
+
         >>> A = pymc.Normal('A',0,1,size=10)
         >>> pprod = pymc.pfunc(numpy.prod)
         >>> B = pprod(A, axis=0)
@@ -442,7 +442,7 @@ def dtrm_generator(*args, **kwds):
                 parents[fargs[i]] = args[i]
             else:
                 varargs.append(args[i])
-                
+
         if len(varargs)==0:
             eval_fun = func
         else:
@@ -455,13 +455,13 @@ def wrapper(**wkwds_in):
                 wargs.extend(wkwds.pop('varargs'))
                 return func(*wargs, **wkwds)
             eval_fun = wrapper
-        
+
         return pm.Deterministic(eval_fun, doc_str, name, parents, trace=False, plot=False)
     dtrm_generator.__name__ = func.__name__ + '_deterministic_generator'
     dtrm_generator.__doc__ = """
     Deterministic-generating wrapper for %s. Original docstring:
     %s
-    
+
     %s
     """%(func.__name__, '_'*60, func.__doc__)
     return dtrm_generator
@@ -531,8 +531,8 @@ def eval_fun(self, other, op, rt_op):
         # Convert the functions into methods for klass.
         new_method.__name__ = '__'+prefix+op_name+'__'
         setattr(klass, new_method.__name__, UnboundMethodType(new_method, None, klass))
-        
-        
+
+
 def create_rl_lin_comb_method(op_name, klass, x_roles, y_roles):
     """
     Creates a new binary special method with left and right versions, such as

pymc/distributions.py

@@ -1943,12 +1943,10 @@ def von_mises_like(x, mu, kappa):
 
     .. math::
         f(x \mid \mu, k) = \\frac{{e}^{k \\operatorname{cos}\\left(x - u\\right)}}{2 \\pi I0(k)}
-    
-    \mu-\pi<= x <=mu+pi
 
     :Parameters:
       x : float
-        Input data. Must be between mu-pi and mu+pi
+        Input data.
       mu : float
         Mean of the distribution.
       kappa : float

pymc/examples/model_1_missing.py

@@ -42,10 +42,7 @@ def r(s=s, e=e, l=l):
     out[s:] = l
     return out
 
-<<<<<<< .mine
+
 # Where the mask is true, the value is taken as missing.
 masked_data = np.ma.masked_array(disasters_array, disasters_mask)
 D = ImputeMissing('D', Poisson, masked_data, mu=r)
-=======
-# Where the value is -999, the datum is assumed to be missing.
-D = Impute('D', Poisson, disasters_array, missing=-999, mu=r)>>>>>>> .r1155

pymc/flib.f

@@ -2879,7 +2879,7 @@ SUBROUTINE vonmises(x,mu,kappa,n,nmu, nkappa, like)
       DOUBLE PRECISION like
       DOUBLE PRECISION tmp
       DOUBLE PRECISION x(n),mu(nmu),kappa(nkappa)
-      DOUBLE PRECISION mu_tmp, kappa_tmp, dev
+      DOUBLE PRECISION mu_tmp, kappa_tmp
       LOGICAL not_scalar_mu, not_scalar_kappa
       DOUBLE PRECISION PI
       PARAMETER (PI=3.141592653589793238462643d0) 
@@ -2897,17 +2897,12 @@ SUBROUTINE vonmises(x,mu,kappa,n,nmu, nkappa, like)
       do i=1,n
         if (not_scalar_mu) mu_tmp=mu(i)
         if (not_scalar_kappa) kappa_tmp=kappa(i)
-        dev = dabs(x(i)-mu_tmp)
-        if (dev .GT. PI) then
-            like = -infinity
-            RETURN
-        endif
         if (kappa_tmp .LT. 0.0) then
           like = -infinity
           RETURN
         endif
         like = like - dlog(2*PI*i0(kappa_tmp))
-        like = like + kappa_tmp*dcos(dev)
+        like = like + kappa_tmp*dcos(x(i)-mu_tmp)
       enddo
       return
       END